Field of Invention
The present invention relates generally to the detection of signal leakage from a Hybrid Fiber-Coax (HFC) network, and more particularly to a method and system for detecting leakage of orthogonal frequency division multiplexing (OFDM) signals and locating the source of the leak in a modern HFC network having a Converged Cable Access Platform (CCAP) architecture.
Background Art
The task of detecting leakage from a coaxial cable part of an HFC network is important for preventing interfering signals emitted from the HFC network (“egress”) at aeronautical and long term evolution (LTE) bands and also for preventing interfering signals from entering the HFC network (“ingress”). The leakage detection in a modern HFC network with a CCAP architecture presents challenges, primarily because of two factors. The first is the aggressive migration from analog to digital signals, such as QAM signals. A QAM signal looks like noise, which creates difficulties in detecting this type of signal by traditional, narrowband analog leakage detectors. Another type of digital signal, introduced under the Data-Over-Cable Service Interface Specifications (DOCSIS) 3.1 specification, published by Cable Television Laboratories, Inc. (CableLabs®) of Louisville, Colo., is a wideband (up to 192 MHz) OFDM signal. The OFDM signal also looks like noise and its detection, e.g., by a sensitive spectrum analyzer, is even more complicated than a QAM signal, because the OFDM signal does not have a 6 MHz haystack spectrum shape (as does the QAM signal).
The second factor making leakage detection in a modern HFC network a challenge is the structure and operation of the CCAP architecture being adopted for such networks. There are many aspects of CCAP architectures, but, from the point of view of detecting radio frequency (RF) leakage, the focus is on the aspect of increasing the number of narrowcast channels (SDV, VOD, DOCSIS, etc.) and forming a full spectrum of downstream channels at a single RF port of a Cable Modem Termination System (CMTS) card, for only a group of nodes or even a single node. In other words, the RF signal spectrum is becoming more unique at each node or group of nodes and this presents greater difficulties for valid detection of RF leakage throughout the HFC network.
The known methods of detecting leakage of digital signals in an HFC network can be divided into three main groups. The first group includes the traditional spectrum analyzer method. This method is universal for detection of any RF signal, but it is not sensitive enough for noise-like, low level QAM and OFDM signals, and there is the difficulty in identifying the particular HFC network (e.g., in an overbuilt scenario) from which the leaked signal came. Also, the cost of such equipment can be relatively high. Further, this method requires a human operator for analysis of the signals. Thus, it is not suitable for an automatic patrolling mode of leakage detection.
The second group of leakage detection methods is based on the injection into the HFC network of some predefined pilot or test signal with specific tag information modulated thereon (i.e., “tag signal”). This group has been well-known for many years and was widely used for detecting leakage of analog signals. Examples of this group are found in the following patents: U.S. Pat. No. 6,600,515 to Bowyer et al.; and U.S. Pat. No. 4,072,899 to Shimp. The use of tag or pilot signals in connection with analog TV signals are disclosed in the following patents: U.S. Pat. No. 6,804,826 to Bush et al.; U.S. Pat. No. 6,600,515 to Bowyer et al.; and U.S. Pat. No. 6,018,358 to Bush. These patents are primarily concerned with analog leakage signal detection, but can be used for digital leakage detection if an unoccupied channel or gap in the HFC spectrum is allocated for the tag or pilot signal (preferably near a digital channel). So, in general, the use of tag and pilot signals in an HFC network is well-known in RF engineering practice.
The first publication, to the Inventor's knowledge, of the idea of injecting a CW pilot carrier into a guard band between two adjacent QAM channels in an all-digital HFC network is a Polish Patent App. No. P.391095, filed Apr. 29, 2010 and a corresponding U.S. Pub. Patent App. No. 2011/0267474 (Nov. 3, 2011), filed Dec. 15, 2010 (by KABELKOM SP.). Similar concepts are also disclosed in the following patent documents: U.S. Pat. No. 8,749,248 (Jun. 10, 2014); and PCT Pub. App. WO 2013003301 (Jan. 3, 2013). In some disclosed embodiments, two CW carriers with a frequency off-set therebetween are used as a composite tag signal.
Another variant of injecting a pilot signal between adjacent QAM channels uses a spread spectrum BPSK modulated pilot signal placed in the guard bands between the QAM channels. This system is described in U.S. Pub. Patent App. 2014/0105251 (Apr. 17, 2014). Using a spread spectrum pilot purportedly makes the detection of the pilot signal more robust. However, the spread spectrum receiver used to accomplish the detection is more complex than a simple FFT receiver used to detect CW pilots in the other solutions.
The main disadvantage of all of the above pilot signal methods is that extra signals must be injected into the HFC network. So, there is a potential risk of the pilot signals interfering with the network's normal commercial signal traffic. In the case of using OFDM signals in an HFC network, the injection of any additional pilot signals may have an impact on the efficiency of data transmission. Also, in a modern HFC network with a CCAP architecture, physically combining any pilot signal with the downstream spectrum, formed at one RF port of a CMTS card for one or small group of nodes, is not trivial and may not even be possible, especially in the case of Fiber Deep systems proposed by Aurora Networks, Santa Clara, Calif. (www.aurora.com).
A third approach to detecting digital signal leakage is based on a coherent cross-correlation method described in U.S. Pat. No. 8,456,530, issued to the Inventor herein. A commercial embodiment of such a method is supplied by ARCOM DIGITAL, LLC, Syracuse, N.Y., under the brand name QAM Snare®. This method is based on the steps: (1) sampling the downstream digital signals at the headend under synchronization of a stable GPS clock; (2) transmitting those samples to a field leakage detector via a wireless IP network; and (3) coherently cross-correlating those samples with samples of a received over-the-air leakage signal. The leakage signal is detected under noisy conditions from a cross-correlation peak resulting from the cross-correlation. The advantage of this method is that there is no need to inject a tag or pilot signal into the HFC network. Also, this method works and is compatible with any noise-like digital signal, such as a QAM or OFDM signal.
Another advantage of the coherent cross-correlation method is that it allows one to measure the time delay of the QAM or OFDM signal from the headend to the leakage detector, and then to use this time delay to determine a location of the leak in the HFC network. The location may be determined by using a Time Difference of Arrival (TDOA) algorithm or predetermined time delays of network devices in the HFC network under test, where the time delays are stored in a network database (“network database method”). Again, refer to the Inventor's earlier patent, U.S. Pat. No. 8,456,530, which is incorporated herein by reference. A limitation (in some circumstances) of the coherent cross-correlation method is that equipment for sampling the downstream digital signal is installed at the headend (or other suitable reference point in the network), and that such a method is most suited for detecting leakage of broadcast channel signals. As indicated above, a trend in modern HFC networks with a CCAP architecture is to reduce the number of broadcast channels, and the adoption of wideband OFDM signals may exacerbate the problem. Because OFDM modulation is more robust than QAM signals in the face of network impairments in the forward path, and due to better efficiencies in data transmission, it is likely that OFDM signals will gradually displace the current QAM channels signals in HFC networks and occupy the forward path spectrum more and more.
A non-coherent cross-correlation method for detecting leakage of a QAM signal has been proposed in U.S. Pub. Patent App. 2013/0322569 (Dec. 5, 2013). The QAM signal is detected by detecting a spectral component of a received signal that corresponds to a known QAM symbol rate used in the HFC network under test. It is believed that this approach is akin to detecting QAM leakage signals using a spectrum analyzer.
A potential problem inherent to known cross-correlation methods is that a physical connection to a large number of RF ports at multiple CMTS's (in a CCAP architecture), for sampling the downstream OFDM signals, may become increasingly difficult, and it may even become impossible with a migration of CCAP to a Fiber Deep architecture. Another potential problem with known cross-correlation methods is that they may require a continuous wireless connection for transmission of reference signal samples from the headend (or other reference point) to the leakage detector in the field. There are still places where wireless communication is not reliable.
In light of the above discussion, it becomes clear that modern HFC networks employing CCAP architecture and transmitting OFDM signals present new challenges to cable operators in detecting and locating leakage of HFC network signals. It should be noted that challenges associated with detecting OFDM signals also exists in “Cognitive radio” and “Spectrum sensing” wireless communication systems. Using those terms in a Google® search will yield a number of articles, books, patents, and other references on this subject. See for example: Shi et al., Improved Spectrum Sensing for OFDM Cognitive Radio in the Presence of Timing Offset, pp. 1-9, 19 Dec. 2014, EURASIP Journal on Wireless Communications and Networking, Vol. 2014, Issue 224; Tripathi, Study of Spectrum Sensing Techniques for OFDM Based Cognitive Radio, pp. 4-8, August 2014, International Journal of Technology Enhancements and Emerging Engineering Research, Vol. 2, Issue 8; Lu et al., Ten Years of Research in Spectrum Sensing and Sharing in Cognitive Radio, pp. 1-16, 31 Jan. 2012, EURASIP Journal on Wireless Communications and Networking, Vol. 2012, Issue 28; Bokharaiee et al., Blind Spectrum Sensing for OFDM-Based Cognitive Radio Systems, pp. 858-71, March 2011, IEEE Transactions on Vehicular Technology, Vol. 60, No. 3, IEEE; Akyildiz et al., Cooperative Spectrum Sensing in Cognitive Radio Networks: A Survey, pp. 40-62, 19 Dec. 2010, Physical Communication, Vol. 2011, Issue 4, Elsevier B.V.; and Yiicek et al., A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications, pp. 116-30, February 2009, IEEE Communications Surveys & Tutorials, Vol. 11, No. 1, First Quarter 2009, IEEE. It is believed that such references concern detection of OFDM signals for wireless communication applications and do not take into account the specifics of an OFDM signal leaking from a coaxial cable part of an HFC network with CCAP architecture. Thus, the known methods of detecting OFDM signals are not directly applicable to solving the above-discussed problems with modern HFC networks employing a CCAP architecture and transmitting OFDM signals.